Technical Field
The disclosed embodiments relate in general to localization and tracking systems and methods and, more specifically, to system and method for optimizing placement and number of Radio Frequency (RF) beacons, such as Bluetooth Low Energy (BLE) beacons, to achieve better indoor localization.
Description of the Related Art
Wireless communication technologies being widespread and ubiquitous have been studied extensively as a solution to indoor positioning systems described in Y. Gu, A. Lo, and I. Niemegeers, “A survey of indoor positioning systems for wireless personal networks,” IEEE Commun. Surv. Tutor., vol. 11, no. 1, pp. 13-32, First 2009. Various solutions using Bluetooth Low Energy (BLE) including M. G. Jadidi, M. Patel, and J. V. Miro, “Gaussian processes online observation classification for RSSI-based low-cost indoor positioning systems,” in Robotics and Automation (ICRA), 2017 IEEE International Conference on, 2017, pp. 6269-6275 and R. Faragher and R. Harle, “Location Fingerprinting With Bluetooth Low Energy Beacons,” IEEE J. Sel. Areas Commun., vol. 33, no. 11, pp. 2418-2428, November 2015, have been proposed which uses Received Signal Strength Indication (RSSI) available from BLE beacons installed in a given environment. In indoor environments, the radio signals are severely impacted due to shadowing and multi-pathing effects, which make the data noisier. In order to receive better RSSI signal from BLEs, they are placed in locations where RSSI signals are available through Line-Of-Sight (LOS) thereby going through minimal multi-pathing. Scaling BLE based indoor positioning becomes a challenging problem as it involves placing beacons at the optimal location to get a high level of localization accuracy. In most of the indoor positioning systems described above, beacons are manually placed using expert knowledge who understands signal behavior due to various environmental conditions. Hence placing BLE beacons optimally has been explored by research experts in sensors networks and robotics community. The optimal BLE map is a function of different parameters such as the number of beacons, the signal broadcast frequency, transmission power, indoor environment, and the required localization accuracy.
Therefore, in view of the aforesaid limitations of the conventional technology, new and improved systems and methods are needed for optimizing placement and number of RF/BLE beacons to achieve better indoor localization.